The significance of field work in remote sensing studies when applied to large areas has often been underestimated. The combination of specific forest inventories for the estimation of aboveground biomass in large dry tropical forest areas with remote sensor data has scarcely been explored to date. In this work, a systematic, stratified forest inventory involving 100 x 100 m square plots in an area of Peruvian Prosopis pallida dry forest, roughly one million hectares in size in the Piura province (Peru) has been compiled. The inventory encompassed the principal silvicultural variables defining the ecosystem studied, which were used in allometric equations for the different species, genera and plant associations in the area in order to estimate the amount of aboveground biomass present in each plot. Field data were related to a Landsat 7 ETM+ image by using six different vegetation indices derived from an image mosaic for the area. Two regression equations (relating the amount of aboveground phytomass to the different vegetation indices) provided reasonably acceptable phytomass predictions for the type of ecosystem concerned (R-2 between 0.72 and 0.52).